Advertisement

Effects of Knowledge Sharing and Social Presence on the Intention to Continuously Use Social Networking Sites: The Case of Twitter in Korea

  • Bong-Won Park
  • Kun Chang Lee
Part of the Communications in Computer and Information Science book series (CCIS, volume 124)

Abstract

Recent surge of social networking websites in the world supports a widely accepted assumption that people aspires to be recognized online by sharing information with others, perceive enjoyment and keeps to use their social networking site continuously. Different from traditional social networking sites (SNSs) like Cyworld and Facebook, Twitter is famous for its short message and ease of sharing knowledge with others in a prompt manner. Therefore, Twitter is preferred most by many people who seem innovative generically. In this sense, Twitter accumulates its fame as the most influential SNS media among users. However, there is no study to investigate why people holds continuous intention to use the Twitter from the perspective of knowledge-sharing and social presence. To resolve this research issue, this paper adopts six constructs such as personal innovativeness, knowledge-sharing intention, perceived ease of use, perceived enjoyment, social presence, and intention to continuously use. Empirical results with 105 valid questionnaires revealed that the proposed research model is statistically significant, and people’s intention to use the Twitter continuously is influenced by social presence, perceived enjoyment, and perceived ease of use.

Keywords

intention to continuously use Personal innovativeness Perceived ease of use knowledge-sharing intention social presence perceived enjoyment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Boyd, D.M., Ellison, N.B.: Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1) (2007), http://jcmc.indiana.edu/vol13/issue1/boyd.ellison.html
  2. 2.
    Helft, M.: Facebook Makes Headway Around the World. The New York Times (2010)Google Scholar
  3. 3.
    Nielson.: Led by Facebook, Twitter, Global Time Spent on Social Media Sites up 82% Year over Year ( 2010), http://blog.nielsen.com/nielsenwire/global/led-by-facebook-twitter-global-time-spent-on-social-media-sites-up-82-year-over-year
  4. 4.
    Niccolai, J.: Biz Stone: Twitter Has 105 Million Users. Macworld (2010), http://www.macworld.com/article/150633/2010/04/twitter.html
  5. 5.
    Strufe, T:. Profile Popularity in a Business-oriented Online Social Network. In: SNS 2010 Workshop, Paris, France (2010). Google Scholar
  6. 6.
    Kwon, O., Wen, Y.: An Empirical Study of the Factors Affecting Social Network Service Use. Computers in Human Behavior 26, 254–263 (2010)CrossRefGoogle Scholar
  7. 7.
    Fogel, J., Nehmad, E.: Internet Social Network Communities: Risk Taking, Trust, and Privacy Concerns. Computers in Human Behavior 25, 153–160 (2009)CrossRefGoogle Scholar
  8. 8.
    Souza, Z.D., Dick, G.N.: Disclosure of Information by Children in Social Networking—Not Just a Case of “You Show Me Yours and I’ll Show You Mine”. International Journal of Information Management 29, 255–261 (2009)CrossRefGoogle Scholar
  9. 9.
    Ebner, M., Reinhardt, W.: Social Networking in Scientific Conferences - Twitter as Tool for Strengthen a Scientific Community. In: Proceedings of the 1st International Workshop on Science 2.0 for TEL at the 4th European Conference on Technology Enhanced Learning (2009)Google Scholar
  10. 10.
    Kwak, H., Lee, C., Park, H., Moon, S.: What Is Twitter, a Social Network or a News Media? In: The Proceedings of the 19th World-Wide Web (WWW) Conference, Raleigh, North Carolina, USA (2010)Google Scholar
  11. 11.
    Benevenuto, F., Rodrigues, T., Cha, M., Almeida, V.: Characterizing User Behavior in Online Social Networks. In: Proceedings of the ACM SIGCOMM Internet Measurement Conference (IMC), pp. 49–62 (2009)Google Scholar
  12. 12.
    Burke, M., Marlow, C., Lento, T.: Feed Me: Motivating Newcomer Contribution in Social Network Sites. Paper presented at ACM CHI 2009: Conference on Human Factors in Computing Systems, Boston, MA (2009) Google Scholar
  13. 13.
    Bhattacherjee, A.: An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance. Decision Support Systems 32(2), 201–214 (2001a)CrossRefGoogle Scholar
  14. 14.
    Bhattacherjee, A.: Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly 25(3), 351–370 (2001b)CrossRefGoogle Scholar
  15. 15.
    Kang, Y.S., Hong, S., Lee, H.: Exploring Continued Online Service Usage Behavior: The Roles of Self-Image Congruity and Regret. Computers in Human Behavior 25(1), 111–122 (2009)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Mäntymäki, M., Salo, J.: Trust, Social Presence and Customer Loyalty in Social Virtual Worlds. In: 23rd Bled eConference eTrust: Implications for the Individual, Enterprises and Society, Bled, Slovenia (2010) Google Scholar
  17. 17.
    Lin, C.S., Wu, S., Tsai, R.J.: Integrating Perceived Playfulness into Expectation–Confirmation Model for Web Portal Context. Information and Management 42(5), 683–693 (2005)CrossRefGoogle Scholar
  18. 18.
    Thong, J.Y.L., Hong, S.-J., Tam, K.Y.: The Effects of Post-Adoption Beliefs on the Expectation–Confirmation Model for Information Technology Continuance. International Journal of Human-Computer Studies 64(9), 799–810 (2006)CrossRefGoogle Scholar
  19. 19.
    Hong, S.-J., Thong, J.Y.L., Tam, K.Y.: Understanding Continued Information Technology Usage Behavior: A Comparison of Three Models in the Context of Mobile Internet. Decision Support Systems 42(3), 1819–1834 (2006)CrossRefGoogle Scholar
  20. 20.
    Agarwal, R., Karahanna, E.: Time Flies When You’re Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage. MIS Quarterly 24(4), 665–694 (2000)CrossRefGoogle Scholar
  21. 21.
    Yi, M.Y., Jackson, J.D., Park, J.S., Probst, J.C.: Understanding Information Technology Acceptance by Individual Professionals: Toward an Integrative View. Information & Management 43, 350–363 (2006)CrossRefGoogle Scholar
  22. 22.
    Lewis, W., Agarwal, R., Sambamurthy, V.: Sources of Influence on Beliefs about Information Technology Use: An Empirical Study of Knowledge Workers. MIS Quarterly 27(4), 657–678 (2003)Google Scholar
  23. 23.
    Hansen, M.T., Nohria, N.: What’s Your Strategy for Managing Knowledge? Harvard Business Review, 106–116 (March-April 1999) Google Scholar
  24. 24.
    Zhaoli, M., Jiong, G.: Knowledge Sharing in Online Communities. In: The 17th European Conference on Information Systems, Verona, Italy (2009) Google Scholar
  25. 25.
    Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology 22, 1111–1132 (1992)CrossRefGoogle Scholar
  26. 26.
    Yi, M.Y., Hwang, Y.: Predicting the Use of Web-based Information Systems: Self-Efficacy, Enjoyment, Learning Goal Orientation, and the Technology Acceptance Model. International Journal of Human-Computer Studies 59, 431–449 (2003)CrossRefGoogle Scholar
  27. 27.
    Short, J., Williams, E., Christie, B.: The Social Psychology of Telecommunications. Jone Wiley, London (1976)Google Scholar
  28. 28.
    Heerink, M., Kröse, B., Wielinga, B., Evers, V.: Enjoyment Intention to Use and Actual Use of a Conversational Robot by Elderly People. In: Proceedings of the 3rd ACM/IEEE International Conference on Human Robot Interaction, New York, NY, USA, pp. 113–120 (2008)Google Scholar
  29. 29.
    Steinbrück, U., Schaumburg, H., Duda, S., Kruger, T.: A Picture Says More Than a Thousand Words-Photographs as Trust Builders in E-commerce Web sites. In: Proceedings of CHI, pp. 748–749 (2002)Google Scholar
  30. 30.
    Cyr, D., Hassanein, K., Head, M., Ivanov, A.: The Role of Social Presence in Establishing Loyalty in e-Service Environments. Interacting with Computers 19, 43–56 (2007)CrossRefGoogle Scholar
  31. 31.
    Davis, F.D.: Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Management Information Systems Quarterly 13(3), 319–339 (1989)CrossRefGoogle Scholar
  32. 32.
    Agarwal, R., Prasad, J.: A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. Information Systems Research 9(2), 204–215 (1998)CrossRefGoogle Scholar
  33. 33.
    Schmitz, J., Fulk, J.: Organizational Colleagues, Media Richness, and Electronic Mail: A Test of the Social Influence Model of Technology Use. Communication Research 18(4), 487–523 (1991)CrossRefGoogle Scholar
  34. 34.
    Sellin, N., Keeves, J.: Path Analysis with Latent Variables. In: Keeves, J.P. (ed.) Educational Research, Methodology, and Measurement: An International Handbook, pp. 633–640. Pergamon, Oxford (1997)Google Scholar
  35. 35.
    Chin, W.W., Newsted, P.R.: Structural Equation Modeling with Small Samples Using Partial Least Squares. In: Hoyle, R.H. (ed.) Statistical Strategies for Small Sample Research, pp. 307–341. Sage, Thousand Oaks (1999)Google Scholar
  36. 36.
    Fornell, C., Larcker, D.: Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research 18(1), 39–50 (1981)CrossRefGoogle Scholar
  37. 37.
    Hars, A., Ou, S.: Working for Free? Motivations for Participating in Open-Source Projects. International Journal of Electronic Commerce 6(3), 25–39 (2002)Google Scholar
  38. 38.
    Aragon, S.R.: Creating Social Presence in Online Environments. New Directions for Adult and Continuing Education 100, 57–68 (2003)CrossRefGoogle Scholar
  39. 39.
    Gefen, D., Straub, D.W.: Consumer Trust in B2C e-Commerce and the Importance of Social Presence: Experiments in e-Products and e-Services. Omega 32(6), 407–424 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Bong-Won Park
    • 1
  • Kun Chang Lee
    • 2
  1. 1.Department of Interaction ScienceSungkyunkwan UniversitySeoulRepublic of Korea
  2. 2.SKK Business School and Department of Interaction ScienceSungkyunkwan UniversitySeoulRepublic of Korea

Personalised recommendations